ieeexplore最新文献_第4页

GPS-Aided Stereo Inertial Navigation Localization Algorithm for Outdoor Scenarios

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-30 DOI: 10.1109/JSEN.2024.3519880

Ying Cai;Fangzheng Gao;Jiacai Huang;Guifang Qiao

{"title":"GPS-Aided Stereo Inertial Navigation Localization Algorithm for Outdoor Scenarios","authors":"Ying Cai;Fangzheng Gao;Jiacai Huang;Guifang Qiao","doi":"10.1109/JSEN.2024.3519880","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3519880","url":null,"abstract":"To address the issues of visual-inertial simultaneous localization and mapping (VISLAM) methods in outdoor environments, such as inevitable drift accumulation during trajectory exploration, loop closure errors due to similar local visual appearances from different perspectives, and degradation of structural features under varying lighting and weather conditions, a tightly coupled GPS-aided visual-inertial SLAM algorithm (TGA-EFG) is proposed in this article. The algorithm enhances the accuracy of the front-end odometry and prior poses by employing the error-state Kalman filter (ESKF) method to fuse GPS measurements, inertial measurement unit (IMU) measurements, and visual measurements for initial value calibration. And then, a sliding window mechanism is introduced the factor graph optimization to overcome the computational redundancy issues of traditional one. In such way, it avoids high-dimensional matrix inversion, thereby improves the overall processing efficiency of the system. The Experimental results launched in both public KITTI dataset and the real environment demonstrate that, comparing our algorithm with mainstream SLAM algorithms, our algorithm improves localization accuracy by 51.63% and processing speed by 12.55%.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"5405-5416"},"PeriodicalIF":4.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fiber Bragg Grating (FBG)-Based Pore Pressure Sensor Utilizing Bellows System

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-30 DOI: 10.1109/JSEN.2024.3521011

W. A. F. W. Burhanuddin;Harith Ahmad;M. S. M. Sa’Ad;M. A. Alias;M. F. Ismail

{"title":"Fiber Bragg Grating (FBG)-Based Pore Pressure Sensor Utilizing Bellows System","authors":"W. A. F. W. Burhanuddin;Harith Ahmad;M. S. M. Sa’Ad;M. A. Alias;M. F. Ismail","doi":"10.1109/JSEN.2024.3521011","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3521011","url":null,"abstract":"This study presents the design, fabrication, and performance evaluation of an optical fiber Bragg grating (FBG)-based pore pressure sensor for geotechnical borehole applications. The sensor comprises a cylindrical body, 3-D, printed from polylactic acid (PLA) material, with dimensions of 40 mm in diameter and 155 mm in length. The transducer holding the FBG utilizes a square bellows design and was 3-D printed using thermoplastic polyurethane (TPU) material, taking advantage of its good flexibility. This transducer was positioned inside a cylindrical housing to allow pore pressure measurement to take place effectively. Two FBGs, denoted FBG P and FBG T, were used to measure pore pressure and temperature, respectively. The experimental results demonstrate a pressure sensitivity of 1.224 pm/kPa for FBG P with a linearity of 99.41%. Besides that, the results also demonstrate FBG T’s effectiveness in giving temperature compensation to FBG P during pore pressure measurement. This innovative sensor design offers a compact and versatile solution for pore pressure measurement in geotechnical applications, combining the benefits of FBG technology with 3-D printing capabilities.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"4706-4714"},"PeriodicalIF":4.3,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Interpretable Heart Disease Detection Model for IoT-Enabled WBAN Systems

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-27 DOI: 10.1109/JSEN.2024.3520866

Damilola D. Olatinwo;Adnan M. Abu-Mahfouz;Gerhard P. Hancke;Hermanus C. Myburgh

{"title":"Interpretable Heart Disease Detection Model for IoT-Enabled WBAN Systems","authors":"Damilola D. Olatinwo;Adnan M. Abu-Mahfouz;Gerhard P. Hancke;Hermanus C. Myburgh","doi":"10.1109/JSEN.2024.3520866","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3520866","url":null,"abstract":"Heart disease is a leading global health concern, contributing to significant mortality rates. It encompasses a range of conditions affecting the heart, leading to complications such as blocked blood vessels, myocardial infarction, chest pain, and stroke. This study presents an interpretable heart disease detection model specifically designed for Internet of Things (IoT)-enabled wireless body area networks (WBANs). Our approach employs a highway bidirectional gated recurrent unit (BiGRU) network to accurately detect heart disease patients. To enhance the model performance, we address critical data preprocessing challenges, such as outliers in data, class imbalance, and feature selection. We employ a robust scaler data transformation method to mitigate the impact of outliers. The synthetic minority oversampling technique (SMOTE) is applied to address the imbalance in the dataset. We utilize the SelectKBest algorithm with the ANOVA F-test scoring function to select the most relevant features to improve the model efficiency. The dataset is partitioned into training, validation, and testing sets to ensure model generalization. Hyperparameter optimization is performed using a random search method to determine the optimal model architecture. Furthermore, a highway network mechanism is incorporated to enhance information flow, leading to improved training efficiency and detection accuracy. To ensure clinical relevance and acceptability, we employ the SHapley Additive exPlanations (SHAP) technique to provide insights into the model’s decision-making process. Evaluation of unseen test data demonstrates that our proposed model outperforms existing approaches by 1%–9% in terms of detection accuracy.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"5457-5469"},"PeriodicalIF":4.3,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SpikePR: Position Regression With Deep Spiking Neural Network

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-27 DOI: 10.1109/JSEN.2024.3520666

Zhao Huang;Yifeng Zeng;Stefan Poslad;Fuqiang Gu

{"title":"SpikePR: Position Regression With Deep Spiking Neural Network","authors":"Zhao Huang;Yifeng Zeng;Stefan Poslad;Fuqiang Gu","doi":"10.1109/JSEN.2024.3520666","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3520666","url":null,"abstract":"Data-driven human localization technology has been on the rise with advancements in end-to-end artificial neural networks (ANNs) in recent years. Different from the traditional pedestrian dead reckoning (PDR) algorithms, the data-driven method can significantly reduce cumulative error over time arising from integration and improve the accuracy and efficiency of localization. However, the computation complexity of ANNs imposes high requirements on hardware conditions and heavily hinders its application on mobile devices. Targeting the above challenges, we design a Position Regression algorithm with a deep spiking neural network (SNN, called SpikePR)—an architecture inspired by biological neurons—to regress the user’s position when collecting a sequence of raw inertial measurement unit (IMU) measurements from mobile devices. This architecture integrates ANNs and SNNs with a leaky integrate-and-fire (LIF) mechanism due to its low-power computation with binary spikes and capability to model the temporal dynamics in time-series data. We conduct extensive experiments on four open-source datasets with the proposed SpikePR algorithm. The experiment results demonstrate that compared to the state-of-the-art position regression algorithms, the proposed SpikePR can save more than 90% energy consumption while achieving similar location errors.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"4350-4359"},"PeriodicalIF":4.3,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study on Model Response of ACFM for Rail RCF Crack Based on Destructive Field Test

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-27 DOI: 10.1109/JSEN.2024.3520832

Chi Wang;Yu Zhou

{"title":"Study on Model Response of ACFM for Rail RCF Crack Based on Destructive Field Test","authors":"Chi Wang;Yu Zhou","doi":"10.1109/JSEN.2024.3520832","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3520832","url":null,"abstract":"The detection of rail rolling contact fatigue (RCF) crack by alternative current field measurement (ACFM) is hindered by the unclear parameters and the relationship between ACFM response and crack parameters. In this article, the response features of ACFM to rail RCF crack parameters are analyzed based on the destructive field test from new rail to 320 million gross ton (MGT) decommission and the established air-crack-rail ACFM model. The morphology and parameters of RCF crack are obtained from CT scan, surface observation, microscope observation, and recalculation of rail blocks sampled with passing gross load of 10, 30, 62, 100, 150, 210, 275, and 320 MGT. The response of ACFM is calculated and extracted at the most significant peak and trough of Bx and Bz. The results show that the crack parameters, surface length (SL), ellipse ratio (ER), and internal angle (IA) of rail RCF crack in eight sampled rail blocks, are 17.2–25 mm, 1.8–6, and 9.1°–38.3°, respectively. The significant response features are comprehensively influenced by all crack parameters. With the change of crack parameters, a clear rule can be found in the response of ACFM features. For the peak of Bx and Bz, the response is dominated by SL followed by ER and IA, and the maximum influences of SL are 85.4% and 77.5%. For the trough of Bx, the responses to internal parameters ER and IA are in a greater proportion. The maximum influences of ER and IA to trough of Bx are 58.1% and 53.8%, respectively.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"4820-4828"},"PeriodicalIF":4.3,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Design of Outer Rotor VR Resolver Based on MEC Model

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-26 DOI: 10.1109/JSEN.2024.3520339

M. R. Soleimani;Z. Nasiri-Gheidari;F. Tootoonchian;H. Oraee

引用次数: 0

A Data-Driven Multiscale Convolutional Adaptive Network for Welding Robot Operating State Recognition

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-26 DOI: 10.1109/JSEN.2024.3519564

Yi He;Weihua Li;Yanzhong Zhang;Kun Xu;Haiyan Wan;Zhuyun Chen

{"title":"A Data-Driven Multiscale Convolutional Adaptive Network for Welding Robot Operating State Recognition","authors":"Yi He;Weihua Li;Yanzhong Zhang;Kun Xu;Haiyan Wan;Zhuyun Chen","doi":"10.1109/JSEN.2024.3519564","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3519564","url":null,"abstract":"The operating states of welding robots are a critical component in the automotive body-in-white assembly process, directly affecting the product quality and production efficiency of the manufacturing line. Therefore, accurate recognition of the operating state patterns is of great importance. Traditional methods relying on sensor signal threshold changes and operator observation are subjective, dependent on human experience, and difficult to implement in intelligent and automated production processes. This study proposes a novel approach to recognize the operating states of welding robots without additional sensors, using a multiscale convolutional adaptive network (MSCAN). First, motion data collection was achieved by leveraging the welding robot’s installed sensors, providing estimates of angular acceleration, angular velocity, and angle of the XYZ-axes. To address the issue of class imbalance in the collected data, the synthetic minority over-sampling technique (SMOTE) algorithm was adopted to generate synthetic samples of the minority class. Then, a MSCAN was constructed, where an attention mechanism was embedded into the convolutional architecture, and a domain adaptation measure was further constructed to mitigate the data distribution discrepancy induced by different operation speeds. Finally, the proposed approach was evaluated and validated on a real welding robot dataset in the body-in-white assembly process. The results showed that the proposed method achieved an accuracy, precision, recall, and <inline-formula> <tex-math>${F}1$ </tex-math></inline-formula>-score of 99.25%, 99.25%, 99.25%, and 99.25%, respectively, outperforming other comparative models. This demonstrates that the proposed model can effectively recognize the operating states of welding robots, possessing significant theoretical and engineering application value in automotive body-in-white assembly.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"5231-5240"},"PeriodicalIF":4.3,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the Importance of the Metal Catalyst Layer to the Performance of CNT-Based Supercapacitor Electrodes 金属催化剂层对碳纳米管超级电容器电极性能的重要性

IF 2.1 4区工程技术

IEEE Transactions on Nanotechnology Pub Date : 2024-12-26 DOI: 10.1109/TNANO.2024.3523412

Kingshuk Chatterjee;Vinay Kumar;Prabhat Kumar Agnihotri;Sumit Basu;Nandini Gupta

{"title":"On the Importance of the Metal Catalyst Layer to the Performance of CNT-Based Supercapacitor Electrodes","authors":"Kingshuk Chatterjee;Vinay Kumar;Prabhat Kumar Agnihotri;Sumit Basu;Nandini Gupta","doi":"10.1109/TNANO.2024.3523412","DOIUrl":"https://doi.org/10.1109/TNANO.2024.3523412","url":null,"abstract":"The power and energy densities of a Supercapacitor (SC) is largely dictated by the accessibility of the nano-porous area of the electrode to the electrolyte ions. Carbon nanotubes (CNT) have high electrical conductivity, and more importantly, may be grown into architectures with high surface area. However, this is not easy to achieve in practice. CNT electrodes are fabricated by chemical vapor deposition (CVD), after a metal catalyst layer is coated on a current collector. In this work, the control of the metal catalyst layer, by varying the dip-coating time and CVD process parameters, is shown to be crucial to pore morphology and consequent SC performance. The dip-coating time is adjusted to obtain thin and uniform coating. Further, optimum reduction of the nickel layer with hydrogen is required to produce thin CNTs with adequate inter-tube separation that facilitate ion accessibility within the pores. The height of the CNT forest is also optimized to prevent decrease in specific capacitance due to reduced accessibility. Proper optimization of the process parameters results in a pore morphology conductive to ion diffusion, and simultaneous improvement in energy and power density.","PeriodicalId":449,"journal":{"name":"IEEE Transactions on Nanotechnology","volume":"24 ","pages":"48-53"},"PeriodicalIF":2.1,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multiple Wi-Fi Sensors Assisted Human Activity Recognition Scheme for Smart Home

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-26 DOI: 10.1109/JSEN.2024.3511087

Jianyang Ding;Yong Wang;Qian Xie;Jiajun Niu

{"title":"A Multiple Wi-Fi Sensors Assisted Human Activity Recognition Scheme for Smart Home","authors":"Jianyang Ding;Yong Wang;Qian Xie;Jiajun Niu","doi":"10.1109/JSEN.2024.3511087","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3511087","url":null,"abstract":"With the development of wireless communication technology, wireless signals have been expanded from mobile communication to behavioral sensing. In particular, human activity recognition (HAR) relying on Wi-Fi signals has attracted increasing attention and demonstrated its great potential in the field of smart healthcare. However, most HAR solutions fail to capture the full scope of the relationship between Wi-Fi signals and human activities. To address this issue, we develop a novel depthwise separable convolution neural network (DSCNN)-based HAR by using channel state information (CSI) of multiple Wi-Fi access points (APs) sensors. To this end, we first introduce an activity-related information enhancement (ARIE) strategy to extract useful information from the CSI and mitigate background noises. Then, we design a multiview CSI fusion (MVCF) approach to calculate key features by aggregating the CSI measurements from all Wi-Fi APs. With this strategy, the feature describes the data themselves more comprehensively than a single view individually. Finally, a DSCNN is used to capture a reliable mapping between the key feature and daily activities, without a scenario-specific calibration. We design and test an HAR prototype on commodity Wi-Fi devices and perform experiments in typical indoor environments. Experimental results confirm that the proposed scheme can achieve accurate and robust HAR compared with existing ones.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"4958-4968"},"PeriodicalIF":4.3,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

STFNET: Sparse Temporal Fusion for 3D Object Detection in LiDAR Point Cloud

IF 4.3 2区综合性期刊

IEEE Sensors Journal Pub Date : 2024-12-26 DOI: 10.1109/JSEN.2024.3519603

Xin Meng;Yuan Zhou;Jun Ma;Fangdi Jiang;Yongze Qi;Cui Wang;Jonghyuk Kim;Shifeng Wang

{"title":"STFNET: Sparse Temporal Fusion for 3D Object Detection in LiDAR Point Cloud","authors":"Xin Meng;Yuan Zhou;Jun Ma;Fangdi Jiang;Yongze Qi;Cui Wang;Jonghyuk Kim;Shifeng Wang","doi":"10.1109/JSEN.2024.3519603","DOIUrl":"https://doi.org/10.1109/JSEN.2024.3519603","url":null,"abstract":"In autonomous driving and robotics, 3D object detection using LiDAR point clouds is a critical task. However, existing single-frame 3D object detection methods face challenges such as noise, occlusions, and sparsity, which degrade detection performance. To address these, we propose the sparse temporal fusion network (STFNet), which leverages multiframe historical information to improve 3D object detection accuracy. The contribution of STFNet contains three core modules: multihistory feature alignment module (MFAM), sparse feature extraction module (SFEM), and temporal fusion transformer (TFformer). MFAM: Ego-motion is used for compensation to align frames, establishing correlations between adjacent frames along the temporal dimension. SFEM: Sparse extraction is performed on features from different time steps to obtain key features within the time series. TFformer: The advanced temporal fusion attention mechanism is introduced to facilitate deep interactions between the current and historical frames. We validated the effectiveness of STFNet on the nuScenes dataset, achieving 71.8% NuScenes detection score (NDS) and 67.0% mean average precision (mAP). Compared to the benchmark method, our method improves 1.6% NDS and 1.5% mAP. Extensive experiments demonstrate that STFNet significantly outperforms most existing methods, highlighting the superiority and generalizability of our approach.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"5866-5877"},"PeriodicalIF":4.3,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0